Image detection template generation method, electronic device, and storage medium

Abstract

The application discloses a method for generating an image detection template, an electronic device and a storage medium, and the method comprises the following steps: acquiring first position information of each detection item in an initial template and first detection configuration information of each detection item; matching each detection item in a second sample to obtain second position information of each detection item in the second sample; determining second detection configuration information based on the first position information of each detection item, the second position information of each detection item and the first detection configuration information of each detection item; and forming an image detection template corresponding to the second sample based on the second position information of each detection item and the second detection configuration information of each detection item. According to the method, the related parameter data of the original initial template and the sample are acquired, and the parameter adjustment of a new sample is automatically completed based on image positioning and image matching, so that the new image detection template is quickly and accurately generated, the manual labor is reduced, and the production efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of image detection, and particularly relates to a method for generating an image detection template, an electronic device, and a storage medium. BACKGROUND

[0002] A valuable security image detection system and an online / offline quality detection device system formed by the same are used for quality detection of small-size printed products such as small-size banknotes and bills. In the prior art, a face array camera or a line array camera is generally used to collect gray scale or RGB three-color images of a product in one or more imaging modes such as white light reflection, white light transmission, infrared reflection, infrared transmission, and ultraviolet fluorescence. An embedded system, an industrial computer, or a server is used to detect the gray scale or RGB three-color images based on an image detection template to realize functions such as OCR (Optical Character Recognition), length-width size measurement, product corner integrity detection, printed image position / size measurement, printed image integrity detection, and printed defect detection.

[0003] In the prior similar device system, when a new quality detection device system is put into use or the current device system needs to detect a new printed product, there are two methods to make a template: (1) based on the detection template of the printed product in another same-type quality detection device system, a master sample is replaced, one or more setting operations and parameter configurations are manually adjusted, and regions, shapes, positions, parameters, and the like involved in manual adjustment operations are manually adjusted to obtain a new detection template; and (2) based on the current device system, a master sample of the printed product is collected, one or more setting operations and parameter configurations are manually completed, and a new detection template suitable for the current system is obtained.

[0004] The inventor finds that the prior similar technology needs manual confirmation of each operation, and the manual operation may have certain parameter input errors and inaccuracy in positioning regions, positioning points, and the like, and also consumes a large amount of time and manpower. SUMMARY

[0005] Embodiments of the present application aim to at least solve one of the above technical problems.

[0006] In a first aspect, embodiments of the present application provide a method for generating an image detection template, comprising: obtaining first position information of each detection item in an initial template and first detection configuration information of the each detection item, wherein the initial template is an image detection template corresponding to a first sample; matching the each detection item in a second sample to obtain second position information of the each detection item in the second sample; determining second detection configuration information of each detection item based on the first position information of the each detection item, the second position information of the each detection item, and the first detection configuration information of the each detection item; and forming an image detection template corresponding to the second sample based on the second position information of the each detection item and the second detection configuration information of the each detection item.

[0007] In a second aspect, an embodiment of the present application provides an electronic device, comprising at least one processor, and a memory connected with the at least one processor in communication, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method for generating an image detection template according to any one of the above aspects of the present application.

[0008] In a third aspect, an embodiment of the present application provides a storage medium, wherein the storage medium stores one or more programs including execution instructions, and the execution instructions are readable and executable by an electronic device (including but not limited to a computer, a server, or a network device, etc.) to perform the method for generating an image detection template according to any one of the above aspects of the present application.

[0009] In a fourth aspect, an embodiment of the present application further provides a computer program product, comprising a computer program stored on a storage medium, and the computer program comprises program instructions, and when the program instructions are executed by a computer, the computer is enabled to perform the method for generating an image detection template according to any one of the above aspects.

[0010] The embodiment of the present application realizes the rapid and accurate generation of a new image detection template by acquiring relevant parameter data of an original initial template, combining image matching technology, and intelligently and automatically completing parameter adjustment of the new template, thereby reducing manual labor and improving production efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0011] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings described in the following are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without any creative labor on the basis of these drawings.

[0012] Figure 1 Flow chart of an embodiment of the method for generating an image detection template of the present application;

[0013] Figure 2 Flow chart of another embodiment of the method for generating an image detection template of the present application;

[0014] Figure 3 Image detection template schematic diagram of the method for generating an image detection template of the present application;

[0015] Figure 4 Flow chart of the implementation process of the method for generating an image detection template of the present application;

[0016] Figure 5Structure schematic view of an embodiment of the electronic device of the present application. DETAILED DESCRIPTION

[0017] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts should fall into the scope of protection of the present application.

[0018] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflicts.

[0019] The present application can be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types. The present application can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules can be located in local and remote computer storage media including memory storage devices.

[0020] In the present application, "module", "device", "system" and the like refer to relevant entities applied to computers, such as hardware, combination of hardware and software, software or software in execution, etc. In detail, for example, an element can be, but is not limited to, a process running on a processor, a processor, an object, an executable, an execution thread, a program and / or a computer. Also, an application or a script running on a server, the server can be an element. One or more elements can be in an execution process and / or thread, and the elements can be localized on one computer and / or distributed between two or more computers, and can be run by various computer readable media. The elements can also communicate with each other through local and / or remote processes according to signals with one or more data packets, for example, signals from data of a local system, another element in a distributed system, and / or a network through signals with other systems through the Internet.

[0021] Finally, it is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting; it is not intended to exclude methodologies otherwise falling within the scope of the application. That is, any

[0022] The embodiment of the present application provides a method for generating an image detection template, which can be applied to an electronic device. The electronic device can be a computer, a server or other electronic products, and the present application is not limited thereto. The valuable securities can include securities, banknotes and printed matters, and the present application is not limited thereto.

[0023] Please refer to Figure 1 , which shows a method for generating an image detection template according to an embodiment of the present application.

[0024] As shown in Figure 1 , in step 101, first position information of each detection item in an initial template and first detection configuration information of the each detection item are acquired, wherein the initial template is an image detection template corresponding to a first sample;

[0025] In step 102, second position information of the each detection item in a second sample is obtained by matching the each detection item in the second sample;

[0026] In step 103, second detection configuration information is determined based on the first position information of each detection item, the second position information of the each detection item and the first detection configuration information of the each detection item;

[0027] In step 104, an image detection template corresponding to the second sample is formed based on the second position information of the each detection item and the second detection configuration information of the each detection item.

[0028] In the embodiment, for step 101, the first position information of each detection item in the initial template and the first detection configuration information of each detection item are acquired. The initial template is acquired by the parameter data on the sample sheet corresponding to the initial template. The first position information of each detection item is the position and value of the detection item such as the boundary contour, size, positioning core and detection area of the sample sheet. The first detection configuration information of each detection item is the setting and parameter configuration of the initial template, for example, the position and value of the detection item such as the boundary contour, size, positioning core and detection area of the sample sheet corresponding to the initial template and the setting and parameter configuration of the template.

[0029] Then, for step 102, the second position information of each detection item in the second sample is acquired by matching each detection item in the second sample. The second sample is a new sample, and the position and value of the detection item such as the boundary contour, size, positioning core and detection area in the new sample need to be acquired. For example, the position and value of the detection item such as the boundary contour, size, positioning core and detection area of the new sample sheet are calculated by the software according to the initial template and the new sample sheet. The position information of the new sample corresponds to the position information of the original sample.

[0030] Then, for step 103, the second detection configuration information is determined according to the first position information of each detection item, the second position information of each detection item and the first detection configuration information of each detection item. For example, the detection configuration information in the new sample is acquired according to the position information such as the boundary contour, size and positioning core in the original sample, the position information such as the boundary contour, size and positioning core in the new sample and the setting and parameter configuration information in the initial template corresponding to the new sample, which is equivalent to acquiring the setting and parameter configuration of the new template corresponding to the new sample.

[0031] Finally, for step 104, the new template corresponding to the new sample is formed based on the position information such as the boundary contour, size and positioning core of each detection item in the new sample and the setting and parameter configuration of each detection item in the new sample. The new template is a new image detection template, and the new image detection template is used for batch production of new sample sheets.

[0032] The method of the embodiment can automatically complete the parameter adjustment of the new template based on the image positioning and image matching technology by acquiring the related parameter data of the original initial template, and can quickly and accurately generate the new image detection template, reduce the manual labor and improve the production efficiency.

[0033] In some alternative embodiments, the detection items include boundary contours, dimensions, positioning kernels, and detection areas, wherein the detection area includes at least one positioning kernel, and the positioning kernel includes feature images formed by various processes of the securities. The boundary contour and size of the inspection item are the range of the effective image of the product. The search method for the image boundary contour is specified, as well as the upper and lower limits of the product's length, width, tilt, and relative position of features. The positioning kernel is selected from the features or printed graphics formed in the substrate / papermaking, offset printing, gravure printing, screen printing, and coding processes. The parts with clear image features and easy image processing positioning are delineated into a rectangular or irregularly shaped pattern area as the positioning kernel (feature images formed in the substrate, offset printing, gravure printing, screen printing, relief printing, coding, etc. processes). One or more positioning kernels can be set. The inspection area is a defined rectangular or irregularly shaped area as the inspection area. The inspection area contains / binds one or more positioning kernels. The area of ​​the inspection area is generally larger than the area of ​​the positioning kernel. One or more inspection areas are set. The images of each inspection area of ​​the product to be inspected are compared and calculated with the standard image, upper limit image, lower limit image, etc., or their projection curves, mean, variance, extreme values, and other statistical characteristics are calculated and compared with the threshold to obtain the area inspection result (qualified / unqualified / identified as a certain type).

[0034] Please refer to Figure 2 This illustrates another method for generating image detection templates according to an embodiment of the present invention. The flowchart mainly describes the process. Figure 1 The flowchart of the steps further included in step 103, "determine the second detection configuration information based on the first location information of each detection item, the second location information of each detection item, and the first detection configuration information of each detection item".

[0035] like Figure 2 As shown, in step 201, the position of the positioning kernel in the first sample is found, the position of the positioning kernel in the second sample is determined by image matching, and the positioning kernel in the second sample is moved to the position of the positioning kernel in the first sample.

[0036] In step 202, based on the positional movement distance of the positioning core in the second sample, the positioning point and size of the positioning core in the second sample are automatically modified.

[0037] In the embodiment, for step 201, the position of the positioning core in the original sample is found, the position corresponding to the position of the positioning core in the original sample in the new sample is searched by using the image matching technology, the position of the positioning core in the new sample is moved to the corresponding position searched, and the position is defined as the position of the positioning core in the new sample. For example, if the reference value of the initial template is x, the lower limit is -a, and the upper limit is +b, the reference value of the new master sample is x' = x + δ, the lower limit is automatically modified to -(a + δ), and the upper limit is automatically modified to +(b - δ); if the position of the positioning core in the initial template is (x, y) in the master sample, the position of the positioning core is searched to (x', y') in the new master sample by using the image matching method, and the positioning core in the new master sample is moved to the position (x', y').

[0038] For step 202, the positioning points and sizes of the positioning core in the new sample are modified according to the moving distance of the position of the positioning core in the new sample, for example, according to the moving distance, the reference value of the initial template is x, the lower limit is -a, and the upper limit is +b, the reference value of the new master sample is x' = x + δ, the lower limit is automatically modified to -(a + δ), and the upper limit is automatically modified to +(b - δ), and the positioning points and sizes related to the positioning core are automatically modified.

[0039] The method of the embodiment further improves the accuracy of the image template by acquiring the position of the positioning core in the original sample and automatically modifying the position parameters of the positioning core in the new sample based on certain rules.

[0040] In some optional embodiments, the detection region in the new sample is determined according to the positioning points and sizes of the position of the positioning core in the new sample, one or more positioning cores can be arranged in the detection region, the position of the detection region is found through the position of the positioning core, and the detection region is used to compare and calculate the image in the detection region with a standard image, an upper limit image, a lower limit image, or the like, or calculate statistical characteristics such as a projection curve, a mean value, a variance, and an extreme value and compare the statistical characteristics with a threshold value to obtain a region detection result.

[0041] In some optional embodiments, the user's modification of the position information of the detected items in the new sample and / or the configuration information of the detected items in the new sample is acquired, and the position information of the detected items in the new sample and / or the configuration information of the detected items in the new sample is updated based on the user's modification of the position information of the detected items in the new sample and / or the configuration information of the detected items in the new sample. In the formation of the new detection template, the user can modify the position data and size data of the detected items in the new sample. The position information in the original sample and the position information in the new sample both include position data and size data. When some "intelligent" modifications exist uncertainty, such as too much numerical modification, too large movement position, multiple matching results in the search result of the positioning core in the new master sample, etc., the modification is allowed, and the accuracy of the detection template is further improved.

[0042] Further, after the image detection template corresponding to the new sample is formed according to the position information of each detected item in the new sample and the detection configuration information of each detected item in the new sample, the formation process of the image detection template corresponding to the new sample is recorded and / or displayed in a preset manner, which is not limited to data logs, texts, graphics, tables or animations, etc. The recording manner can be local storage or cloud storage, and the display can be displayed through a display device or a smart device with a display screen.

[0043] Before the new image detection template is formed, the optical recognition number position and parameters of the image detection template need to be set.

[0044] Please refer to Figure 3 , which shows a schematic diagram of an image detection template of a generation method of the image detection template, as shown in Figure 3 , the main value and feature of the image detection template is that after the basic template / initial template, according to the initial template and the related parameter data of the sample, combined with image matching technology, intelligent automatic parameter adjustment of the new sample is completed, and the new template can be quickly converted, the operation time is saved, and the production efficiency is improved.

[0045] Please refer to Figure 4 , which shows a realization process flow of the image detection template.

[0046] As shown in Figure 4 , (1) based on a master sample / reference sample / standard sample, the parameters in the sample are acquired to obtain a basic template / initial template;

[0047] (2) when a new quality detection device system is put into use, or a new printing product is to be detected by the current device system, a new master sample / reference sample / standard sample is collected;

[0048] (3) According to the basic template / initial template and the new sample sheet, the software calculates the boundary contour, size, positioning core, and the position and value of the detection items such as detection area of the new sample sheet, and intelligently modifies the settings and parameter configurations of the template according to certain rules to form a new template suitable for the new sample sheet, wherein the settings and parameter configurations can include vertex / corner point, boundary, contour, coordinate position, reference value, detection threshold value, and other template setting items such as positioning core / positioning point associated with vertex / corner point, boundary, contour, and the like, and typical rules are as follows:

[0049] ① For a size measurement, the reference value of the initial template is x, the lower limit is -a, and the upper limit is +b. In the new master sample sheet, the reference value is x' = x + δ, then the lower limit is automatically modified to -(a + δ) and the upper limit is +(b - δ). In the above example, the entire size does not change, and the size deviation range is modified, such as a certain size standard is [154.0, 156.0], the size value of the original master sample sheet is 155.2, and the size deviation range is [-1.2, 0.8]. If the size value of the new master sample sheet is 155.1, the size deviation range is automatically modified to [-1.1, 0.9]. Before and after the modification, the size value of the master sample sheet plus the deviation range is [154.0, 156.0], and the entire size of the new master sample sheet does not change.

[0050] ② For a positioning core, the (x, y) position of the master sample sheet in the initial template, and the (x', y') position of the positioning core is searched in the new master sample sheet by image matching method, then the positioning core is moved to the (x', y') position, and the positioning point and size related to the positioning core are modified according to the moving distance and reference rule ①.

[0051] ③ For a detection area with a reference position (m, n) and a bound positioning core, the bound positioning core is moved from the (x, y) position to the (x', y') position according to rule ②, then the detection area is moved to the (m+x'-x, n+y'-y) position.

[0052] The detection template formation process data is recorded or displayed in the form of log, text, graph, table, animation, etc., and the user is allowed to intervene to modify the position and value of the detection items.

[0053] The image detection template generation method in the application is used for valuable securities, is based on image positioning, image matching and the like, automatically completes parameter adjustment and position adjustment, and can quickly and accurately generate a new image detection template, reduces manual labor, and improves production efficiency. The image positioning can include vertex / corner positioning, the vertex / corner position of the image can be determined through numerical statistics and image numerical projection, rectangular image four-side boundary positioning, the start point, end point and slope of the side can be calculated through image pixel difference, image gradient and straight line fitting, and positioning kernel search positioning, the best matching position of the positioning kernel in the search image can be determined through image difference, image distance and image similarity, which is not limited in the application.

[0054] It should be noted that, for the foregoing method embodiments, in order to simply describe, they are all expressed as a series of actions, but those skilled in the art should know that the present application is not limited by the action sequence described, because according to the present application, certain steps can be performed in other sequences or at the same time. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily necessary for the present application. In the above embodiments, the description of each embodiment is focused on, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0055] In some embodiments, the embodiment of the present application provides a non-volatile computer readable storage medium, the storage medium stores one or more programs including execution instructions, the execution instructions can be read and executed by an electronic device (including but not limited to a computer, a server, or a network device, etc.) to execute the image detection template generation method of any one of the above embodiments of the present application.

[0056] In some embodiments, the embodiment of the present application also provides a computer program product, the computer program product includes a computer program stored on a non-volatile computer readable storage medium, the computer program includes program instructions, when the program instructions are executed by a computer, the computer executes the image detection template generation method of any one of the above embodiments.

[0057] In some embodiments, the embodiment of the present application also provides an electronic device, which includes at least one processor, and a memory connected with the at least one processor in communication, wherein the memory stores instructions executable by the at least one processor, the instructions are executed by the at least one processor to enable the at least one processor to execute the image detection template generation method.

[0058] Figure 5is a schematic diagram of a hardware structure of an electronic device for executing the image detection template generation method provided by another embodiment of the present application, as shown in Figure 5 The device includes:

[0059] one or more processors 510 and a memory 520, Figure 5 In an example, the one processor 510 is taken as an example.

[0060] The device for executing the image detection template generation method can further include an input device 530 and an output device 540.

[0061] The processor 510, the memory 520, the input device 530, and the output device 540 can be connected through a bus or other means, Figure 5 In an example, the connection through the bus is taken as an example.

[0062] The memory 520, as a non-volatile computer readable storage medium, can be used to store non-volatile software programs, non-volatile computer executable programs, and modules, such as program instructions / modules corresponding to the image detection template generation method in the embodiments of the present application. The processor 510 executes various function applications and data processing of the server by running the non-volatile software programs, instructions, and modules stored in the memory 520, that is, implements the image detection template generation method of the above method embodiments.

[0063] The memory 520 can include a program storage area and a data storage area, wherein the program storage area can store an operating system and application programs required by at least one function; the data storage area can store data created according to the use of the image detection template generation device, etc. In addition, the memory 520 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 520 can optionally include a memory remotely arranged with respect to the processor 510, and these remote memories can be connected to the image detection template generation device through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0064] The input device 530 can receive input digital or character information, and generate signals related to user settings and function control of the image detection template generation device. The output device 540 can include a display device such as a display screen.

[0065] The one or more modules are stored in the memory 520, and when executed by the one or more processors 510, execute the image detection template generation method in any of the above method embodiments.

[0066] The product can execute the method provided in the embodiments of the present application, has the corresponding function modules and beneficial effects of executing the method. Technical details not described in detail in the embodiments can be referred to the method provided in the embodiments of the present application.

[0067] The electronic device of the embodiments of the present application exists in various forms, including but not limited to:

[0068] (1) Mobile communication device: The feature of this kind of device is to have mobile communication function, and to provide voice and data communication as the main target. This kind of terminal includes: smart phone, multimedia phone, functional phone, and low-end phone, etc.

[0069] (2) Ultra-mobile personal computer device: This kind of device belongs to the category of personal computer, has computing and processing function, and generally has mobile Internet feature. This kind of terminal includes: PDA, MID and UMPC device, etc.

[0070] (3) Portable entertainment device: This kind of device can display and play multimedia content. This kind of device includes: audio and video player, handheld game machine, electronic book, and smart toy and portable car navigation device.

[0071] (4) Other onboard electronic devices with data interaction function, such as vehicle-mounted device installed on vehicle.

[0072] The device embodiments described above are only schematic, wherein the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, i.e. can be located in one place, or can be distributed on a plurality of network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments.

[0073] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be realized by means of software plus a general hardware platform, and of course can also be realized by hardware. Based on such understanding, the above technical solutions or the part that contributes to the related art can be embodied in the form of software product, which can be stored in a computer readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes a plurality of instructions to make a computer device (which can be a personal computer, server, or network device, etc.) execute the method described in each embodiment or some part of the embodiment.

[0074] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present application, and are not intended to limit the same; although the present application has been described in detail with reference to the foregoing examples, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for generating an image detection template for a security document, comprising: obtaining first position information of each detection item in an initial template and first detection configuration information of the each detection item, wherein the initial template is an image detection template corresponding to a first sample; matching the each detection item in a second sample to obtain second position information of the each detection item in the second sample; determining second detection configuration information based on the first position information of each detection item, the second position information of the each detection item and the first detection configuration information of the each detection item; forming an image detection template corresponding to the second sample based on the second position information of the each detection item and the second detection configuration information of the each detection item; wherein the detection item comprises a boundary contour, a size and a detection area, the detection area comprises at least one positioning core, the positioning core comprises a feature image formed by each process of the security document, and the positioning core is a part selected from a feature formed by a base material / papermaking, offset printing, intaglio printing, screen printing and code printing or a printed image, which has a distinct image feature and is easy to locate in image processing; the determination of the second detection configuration information based on the first position information of each detection item, the second position information of the each detection item and the first detection configuration information of the each detection item comprises: searching for a position of the positioning core in the first sample, determining a position of the positioning core in the second sample by image matching, and moving the positioning core in the second sample to the position of the positioning core in the first sample; and automatically modifying a positioning point and a size of the positioning core in the second sample based on a moving distance of the positioning core in the second sample.

2. The method of claim 1, wherein, the matching of the each detection item in the second sample to obtain the second position information of the each detection item in the second sample comprises: determining a detection area in the second sample based on a positioning point of the positioning core in the second sample and a size of the positioning core.

3. The method of claim 1, wherein, before the forming of the image detection template corresponding to the second sample based on the second position information of the each detection item and the second detection configuration information of the each detection item, further comprising: obtaining a modification of the second position information of at least one detection item by a user and / or a modification of the second detection configuration information of the at least one detection item by the user, and updating the second position information of the at least one detection item and / or the second detection configuration information of the at least one detection item based on the modification of the user.

4. The method of claim 1, wherein, after the forming of the image detection template corresponding to the second sample based on the second position information of the each detection item and the second detection configuration information of the each detection item, further comprising: recording and / or displaying a forming process of the image detection template corresponding to the second sample in a preset manner.

5. The method of claim 1, wherein, the first position information and the second position information both comprise position data and size data.

6. The method of claim 1, wherein, before the forming of the image detection template corresponding to the second sample based on the second position information of the each detection item and the second detection configuration information of the each detection item, further comprising: setting an optical identification number position and a parameter of the image detection template.

7. An electronic device comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the method of any one of claims 1 to 6.

8. A storage medium having stored thereon a computer program, characterized in that The program, when executed by a processor, implements the steps of the method of any one of claims 1 to 6.

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